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Important Dates
  • Full paper submission / Special sessions proposals
    July 31, 2020 August 31, 2020 September 11, 2020
  • Accepted papers notification
    August 31, 2020September 15, 2020
    September 20, 2020
  • Final submission due
    September 15, 2020September 25, 2020
    September 29, 2020
  • Video submission due
    October 20, 2020

TODAY 2021. 10. 20

ICCE-Asia 2020



Prof. Young-Ro Yoon (Yonsei University)

[Nov. 1(Sun) 14:00-15:30, Sicily (1F)]

Status and Prospects of Medical Device Industry in South Korea

From 1971, the development of the domestic medical device industry had momentary momentum. In 1971, the domestic medical device industry had 91 companies, a total production value of 500 million won, and medical device imports of 11 million dollars. in Korea, introduced the Medical Insurance System in 1977, and then 1,008 domestic medical device companies, total production of 70 It has grown to KRW 37.2 million, with medical device imports of KRW 37.2 million.

In 1985, Medison was established as a representative medical device company, and in 1987, the Ministry of Commerce, which is the predecessor of the Ministry of Trade, Industry and Energy, launched a catch-place “Let's get out of the underdeveloped country in the medical device industry” and prepared comprehensive promotion measures to develop industrial-based technology. In 1995, the Ministry of Health and Welfare developed and fostered the domestic medical device industry through “Health and Medical Technology R&D Project” in which medical engineers, doctors, and companies participated together, and “G7 Project Project” in 1996.

The Ministry of Food and Drug Safety announced on May 20, 2020 that “in 2019, the domestic medical device production performance increased by 11.8% to 7,279.4 billion won, compared to 2016 (6,511.1 billion). The size of the domestic medical device market has been growing at an annual average of 10.3% over the past five years to 7.8 trillion won in 2019.

Through this topic, we will try to predict the future through analysis of the past and present of the Korean medical device industry through the current status and future outlook of the Korean medical device industry.

Professor Young Ro Yoon is currently a professor of dept. Biomedical Engineering, at Yonsei University's School of Health Sciences since February 1994. He served as a visiting professor at University of Florida Gainesville from August 2001 to July 2002, and as a visiting professor at the University of California, San Diego, from February 1, 2010 to January 2011. He received a bachelor's degree in electronic engineering from Yonsei University in 1981 and a master's degree in electrical engineering from California State University in Los Angeles in 1986. He received a Ph.d. in School of electrical engineering from Purdue University in 1991. He has worked as an engineer at Dynatrol National Corp. USA from 1985 to 1986 and as a researcher at the US Naval Research Laboratory in San Diego USA from March 1992 to January 1994. He has been working as a food and drug policy advisor from the Ministry of Food and Drug Safety from April 2017 to the present. He received the Prime Minister's citation on December 5, 2013 and the President's citation on May 29, 2017. Other awards include the Gangwon-do Governor's Citation on November 10, 2017, Wonju Mayor's Citation on October 25, 2007, the Biomedical Engineering Award on November 18, 2018 and December 2, 2005, and the 2018 Korea Medical Device Industry Association Appreciation Plaque. He localized the ear thermometer for the first time in Korea. He has many industrialization results and related patents.

Prof. Shogo Muramatsu (Niigata University)

[Nov. 1(Sun) 16:00-17:30, Sicily (1F)]

Sparsity-Aware High-Dimensional Data Restoration with Convolutional Dictionary Learning

In this tutorial, sparsity-aware restoration process of high-dimensional data is outlined. First, the purpose and application examples of image and volumetric data restoration are introduced. Then, the relationship between simultaneous equations and signal restoration is illustrated. The following topics are also summarized: Inner products and filtering, linear systems and matrices, filter banks and synthesis dictionaries, sparse modeling and MAP estimation, image generation and prior knowledge. Convolutional dictionary learning is also explained in connection with the design of parametric filter banks. Finally, the nonlinear extension of convolution dictionary is discussed and compared with convolutional neural networks (CNNs).

Shogo Muramatsu received the B.E., M.E. and Ph.D. degrees from Tokyo Metropolitan University, Tokyo, Japan, in 1993, 1995 and 1998, respectively. From 1997 to 1999, he worked at Tokyo Metropolitan University. In 1999, he joined Niigata University, where he is currently a Professor in the Faculty of Engineering. From 2003 to 2004, he was a Visiting Researcher at the University of Florence, Italy. His research interests include multidimensional signal processing, multi-rate systems, image processing, video analysis, and embedded vision systems. Prof. Muramatsu is a Senior Member of IEEE and IEICE (Institute of Electronics, Information, and Communication Engineers of Japan) and a Member of APSIPA (Asia-Pacific Signal and Information Processing Association) and ITE (Institute of Image Information and Television Engineers of Japan). He is an Associate Editor for the IEEE Transactions on Signal Processing since 2019 and an APSIPA Distinguished Lecturer from 2020 to 2021.

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